Decoding Music Attention from “EEG Headphones”: A User-Friendly Auditory Brain-Computer Interface - An, Winko W.; Shinn-Cunningham, Barbara; Gamper, Hannes; Emmanouilidou, Dimitra; Johnston, David; Jalobeanu, Mihai; Cutrell, Ed; Wilson, Andrew D.; Chiang, Kuan-Jung; Tashev, Ivan (ICASSP 2021, 2021)
People enjoy listening to music as part of their life. This makes music an excellent choice for designing a user-friendly brain-computer interface (BCI) for long-term use. We propose a novel BCI system using music stimuli that relies on brain signals collected via Smartfones, an EEG recording device integrated into a pair of headphones. In a user study of the proposed system, participants were asked to pay attention to one of three musical instruments playing simultaneously from separate spatial directions. We used a stimulus reconstruction method to decode attention from EEG signals. Results show that the proposed system can achieve good decoding accuracy (>70%) while providing superior user-friendliness compared to a traditional EEG setup.